Siloed Perceptions in Pharmaceutical Supply Chain Risk Management: A Brazilian Perspective

Silva, Jéssica; Araújo, Claudia Affonso Silva; Marques, Leonardo

doi:10.1080/10978526.2020.1731315

Cited by 15 publications

(17 citation statements)

References 59 publications

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“…Silva et al. (2020) conducted a study where they employed the Orders-of-magnitude AHP to identify and prioritize risks from the perspectives of different players in the industry, such as industry, distributors and buyers.…”

Section: Literature Reviewmentioning

confidence: 99%

“…infrastructure failure was identified as the most critical sub-risk in cold chain technology. Silva et al (2020) conducted a study where they employed the Orders-of-magnitude AHP to identify and prioritize risks from the perspectives of different players in the industry, such as industry, distributors and buyers. Their findings revealed that R&D incapability was the most critical risk within the industry, with quality and poor inventory management ranking as the second and third important risks, respectively.…”

Section: Critical Risks In Pharmaceutical Industrymentioning

confidence: 99%

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Analyzing pharmaceutical industry risks under uncertainty for performance improvement: an Indian scenario

Sharma,

Kumar,

Arora

2023

BPMJ

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PurposeThe pharmaceutical industry faces multiple risks that adversely affect its performance. Within these risks, some dependencies have been observed, which help in streamlining the mitigation efforts. Therefore, the present work identifies and categorizes various risks/sub-risks in cause–effect groups, considering uncertainty in the decision-making process.Design/methodology/approachAn extensive literature review and experts' opinions were utilized to identify and finalize the risks faced by the pharmaceutical industry. For further analysis, data collection was done using a questionnaire focusing on finalized risks. Based on the data, the causal relation under uncertainty between various risks/sub-risks was identified using a multi-criteria decision making (MCDM) technique, i.e. intuitionistic fuzzy DEMATEL, in a pairwise manner.FindingsThe results show that the three most prominent risk categories are operational, demand/customer/market and financial. Also, out of the seven main risks, only supplier and operational are categorized within the effect group and the rest, i.e. financial, demand, logistics, political and technology within the cause group. The sub-risks within each category have also been categorized into cause–effect groups. The mitigation of cause group risks will help in economize the financial resources and improve the performance and resilience of the industry.Originality/valueThere is insufficient research on identifying the causality among the pharmaceutical industry risks. Additionally, an extensive discussion on the identified cause–effect groups is also missing in the literature. Therefore, in this work, efforts have been made to determine the prominent risks for the Indian pharmaceutical industry that will be helpful for channelizing the resources to mitigate risks for a resilient industry.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Critical Risks In Pharmaceutical Industrymentioning

confidence: 99%

Analyzing pharmaceutical industry risks under uncertainty for performance improvement: an Indian scenario

Sharma,

Kumar,

Arora

2023

BPMJ

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“…In the study, personnel recruitment, purchasing of pharmaceutical and packaging components, facility design and operation, cleaning and disinfection, utilities, production processes, packaging and labeling, storage, shipping, distribution and patient usage parameters were evaluated according to good manufacturing practices, [6]. Silva et al (2020) defined the risks in the pharmaceutical supply chain of Brazil and proposed an approach based on the AHP method to define their risk magnitudes, [35]. Lawrence et al (2020) conducted a study investigating the effect of severe weather conditions on the disruption of the pharmaceutical supply chain, [22].…”

Section: Literature Review On Pharmaceutical Supply Chain Problemmentioning

confidence: 99%

Pharmaceutical 3PL supplier selection using interval-valued intuitionistic fuzzy TOPSIS

Kahraman¹,

Çebı²,

Onar³

et al. 2022

NIFS

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Third party logistics (3PL) supplier selection problem is a multi-criteria selection problem that is frequently discussed in the literature. Medicine is a fundamental element for human health and drug transportation must be carried out on time and under conditions that will ensure that the drug does not lose its physical properties. Therefore, the pharmaceutical industry is one of the foremost and most important sectors in 3PL. In this multi-criteria problem where the evaluation criteria are linguistic rather than numerical, vagueness and impreciseness in evaluations can only be handled with the help of fuzzy sets. With the help of intuitionistic fuzzy sets, one of the new extensions of fuzzy sets, the vagueness and impreciseness here will be discussed and the 3PL supplier selection problem will be tried to be solved with the TOPSIS method, which is one of the most used MCDM methods in the literature. The use of Interval-Valued Intuitionistic Fuzzy sets will add more flexibility and accuracy to the assessment. Thus, the Interval-Valued Intuitionistic Fuzzy TOPSIS method is used to solve the 3PL supplier selection problem and the robustness of the decisions taken is tested with a sensitivity analysis.

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“…Ahmad et al (2021d), Salehi et al (2020) and Settanni et al (2017) proposed a fuzzy mathematical model for performance assessment of PSC by a unique resilience engineering and do not cover the reliability level demand and multiple DCs. The analysis of PSC risk management in Brazilian perspectives is performed in Silva et al (2020), but the critical risk of supplying pharmaceutical products at the time of emergency was left untouched.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The health-care supply chain shows that there are some crucial contributions that can be added to the problem and make it more realistic. In most of the PSC models discussed in the literature, all the customers’ demand is allocated only to the DCs (Salehi et al , 2020; Settanni et al , 2017; Silva et al , 2020). Sometimes the supply cannot be provided reasonably because of capacity constraints, time limitations, inventory shortages, etc.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy quantitative model for assessing the performance of pharmaceutical supply chain under uncertainty

Ahmad

John

2021

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PurposeThis study aims to investigate a reliability-level demand-oriented pharmaceutical supply chain design with maximal anticipated demand coverage. Different hospitals with the particular reliability value associated with the various pharmaceutical items (PIs) are considered. An inter-connected multi-period supply chain comprising manufacturers, distribution centers, hospitals and patients is assumed for the smooth flow of health-care items, enhancing supply chain reliability. A reliability index for PIs is depicted to highlight product preference and facilitate hospitals’ service levels for patients.Design/methodology/approachA mixed-integer multi-objective programming problem that maximizes maximal demand coverage minimizes the total economic costs and pharmaceutical delivery time is depicted under intuitionistic fuzzy uncertainty. Further, a novel interactive neutrosophic programming approach is developed to solve the proposed pharmaceutical supply chain management (PSCM) model. Each objective’s marginal evaluation is elicited by various sorts of membership functions such as linear, exponential and hyperbolic types of membership functions and depicted the truth, indeterminacy and falsity membership degrees under a neutrosophic environment.FindingsThe proposed PSCM model is implemented on a real case study and solved using an interactive neutrosophic programming approach that reveals the proposed methods’ validity and applicability. An ample opportunity to generate the compromise solution is suggested by tuning various parameters. The outcomes are evaluated with practical managerial implications based on the significant findings. Finally, conclusions and future research scope are addressed based on the proposed work.Research limitations/implicationsThe propounded study has some limitations that can be addressed in future research. The discussed PSCM model can be merged with and extended by considering environmental factors such as the health-care waste management system, which is not included in this study. Uncertainty among parameters due to randomness can be incorporated and can be tackled with historical data. Besides, proposed interactive neutrosophic programming approach (INPA), various metaheuristic approaches may be applied to solve the proposed PSCM model as a future research scope.Practical implicationsThe strategy advised is to provide an opportunity to create supply chains and manufacturing within India by helping existing manufacturers to expand, identifying new manufacturers, hand-holding and facilitating, teams of officers, engineers and scientists deployed and import only if necessary to meet timelines. Thus, any pharmaceutical company or organization can adopt the production and distribution management initiatives amongst hospitals to strengthen and enable the pharmaceutical company while fighting fatal diseases during emergencies. Finally, managers or policy-makers can take advantage of the current study and extract fruitful pieces of information and knowledge regarding the optimal production and distribution strategies while making decisions.Originality/valueThis research work manifests the demand-oriented extension of the integrated PSCM design with maximum expected coverage, where different hospitals with pre-determined reliability values for various PIs are taken into consideration. The practical managerial implications are explored that immensely support the managers or practitioners to adopt the production and distribution policies for the PIs to ensure the sustainability in supply chain design.

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Siloed Perceptions in Pharmaceutical Supply Chain Risk Management: A Brazilian Perspective

Cited by 15 publications

References 59 publications

Analyzing pharmaceutical industry risks under uncertainty for performance improvement: an Indian scenario

Analyzing pharmaceutical industry risks under uncertainty for performance improvement: an Indian scenario

Pharmaceutical 3PL supplier selection using interval-valued intuitionistic fuzzy TOPSIS

A fuzzy quantitative model for assessing the performance of pharmaceutical supply chain under uncertainty

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